Analyzing Risk Factors for Fatality in Urban Traffic Crashes: A Case Study of Wuhan, China

How to maintain public transit safety and sustainability has become a major concern for the department of Road Traffic Administration. This study aims to analyze the risk factors that contribute to fatality in road traffic crashes using a 5-year police-reported dataset from the Wuhan Traffic Management Bureau. Four types of variables, including driving experience, environmental factor, roadway factor and crash characteristic, were examined in this research by a case-control study. To obtain a comprehensive understanding of crash fatality, this study explored a detailed set of injury-severity risk factors such as impact direction, light and weather conditions, crash characteristic, driving experience and high-risk driving behavior. Based on the results of statistical analyses, fatality risk of crash-involved individuals was significantly associated with driving experience, season, light condition, road type, crash type, impact direction, and high-risk driving behavior. This study succeeded in identifying the risk factors for fatality of crash-involved individuals using a police-reported dataset, which could provide reliable information for implementing remedial measures and improving sustainability in urban road network. A more detailed list of explanatory variables could enhance the accountability of the analysis.

[1]  Kelvin K W Yau,et al.  Risk factors affecting the severity of single vehicle traffic accidents in Hong Kong. , 2004, Accident; analysis and prevention.

[2]  J Ozanne-Smith,et al.  Injury-related fatalities in China: an under-recognised public-health problem , 2008, The Lancet.

[3]  N N Sze,et al.  Diagnostic analysis of the logistic model for pedestrian injury severity in traffic crashes. , 2007, Accident; analysis and prevention.

[4]  G. Rizzo,et al.  Improving the Sustainability of Transportation: Environmental and Functional Benefits of Right Turn By-Pass Lanes at Roundabouts , 2015 .

[5]  Qingyun Du,et al.  A Network-Constrained Integrated Method for Detecting Spatial Cluster and Risk Location of Traffic Crash: A Case Study from Wuhan, China , 2015 .

[6]  Mohamed Abdel-Aty,et al.  Presence of passengers: does it increase or reduce driver's crash potential? , 2008, Accident; analysis and prevention.

[7]  David Bishai,et al.  Road Traffic Injury in China: A Review of National Data Sources , 2012, Traffic injury prevention.

[8]  Hoong Chor Chin,et al.  Severity of driver injury and vehicle damage in traffic crashes at intersections: a Bayesian hierarchical analysis. , 2008, Accident; analysis and prevention.

[9]  Ramesh Sharda,et al.  Identifying significant predictors of injury severity in traffic accidents using a series of artificial neural networks. , 2006, Accident; analysis and prevention.

[10]  Wei Wu,et al.  Designing Sustainable Public Transportation: Integrated Optimization of Bus Speed and Holding Time in a Connected Vehicle Environment , 2016 .

[11]  Gabriel Brătucu,et al.  Road Safety Education in the Context of the Sustainable Development of Society: The Romanian Case , 2016 .

[12]  Daniel Sun,et al.  Vulnerability Analysis of Urban Rail Transit Networks: A Case Study of Shanghai, China , 2015 .

[13]  Fred Mannering,et al.  Impact of roadside features on the frequency and severity of run-off-roadway accidents: an empirical analysis. , 2002, Accident; analysis and prevention.

[14]  Andrew Hayen,et al.  The impact of environmental, vehicle and driver characteristics on injury severity in older drivers hospitalized as a result of a traffic crash. , 2008, Journal of safety research.

[15]  Gudmundur F. Ulfarsson,et al.  Driver-injury severity in single-vehicle crashes in California: A mixed logit analysis of heterogeneity due to age and gender. , 2013, Accident; analysis and prevention.

[16]  F. Rivara,et al.  Changes in traffic crash mortality rates attributed to use of alcohol, or lack of a seat belt, air bag, motorcycle helmet, or bicycle helmet, United States, 1982–2001 , 2006, Injury Prevention.

[17]  Mohamed Abdel-Aty,et al.  Comprehensive analysis of vehicle-pedestrian crashes at intersections in Florida. , 2005, Accident; analysis and prevention.

[18]  Tonglin Zhang,et al.  A measure of spatial stratified heterogeneity , 2016 .

[19]  Mohamed Abdel-Aty,et al.  Examining traffic crash injury severity at unsignalized intersections. , 2010, Journal of safety research.

[20]  Mohamed Abdel-Aty,et al.  Bayesian random effect models incorporating real-time weather and traffic data to investigate mountainous freeway hazardous factors. , 2013, Accident; analysis and prevention.

[21]  Cao Xin-tao Analysis of Characteristic of Driver Involved in Road Traffic Accident , 2009 .

[22]  Mohamed Abdel-Aty,et al.  Analysis of driver injury severity levels at multiple locations using ordered probit models. , 2003, Journal of safety research.

[23]  Mark Asbridge,et al.  Cell phone use and traffic crash risk: a culpability analysis. , 2013, International journal of epidemiology.

[24]  Dominique Lord,et al.  The statistical analysis of highway crash-injury severities: a review and assessment of methodological alternatives. , 2011, Accident; analysis and prevention.

[25]  D. Stead,et al.  Sustainable Urban Transport in the Developing World: Beyond Megacities , 2015 .

[26]  Hans-Yngve Berg,et al.  A pattern analysis of traffic crashes fatal to older drivers. , 2009, Accident; analysis and prevention.

[27]  Flavio Pechansky,et al.  Traffic Crashes and Alcohol Outlets in a Brazilian State Capital , 2013, Traffic injury prevention.

[28]  Xiaoying Zheng,et al.  Geographical Detectors‐Based Health Risk Assessment and its Application in the Neural Tube Defects Study of the Heshun Region, China , 2010, Int. J. Geogr. Inf. Sci..

[29]  Yuhai Bao,et al.  Geographical Detector Model for Influencing Factors of Industrial Sector Carbon Dioxide Emissions in Inner Mongolia, China , 2016 .

[30]  Thomas L. Traynor The Relationship Between Regional Economic Conditions and the Severity of Traffic Crashes , 2009, Traffic injury prevention.

[31]  Kirolos Haleem,et al.  Identifying Traditional and Nontraditional Predictors of Crash Injury Severity on Major Urban Roadways , 2011, Traffic injury prevention.

[32]  Carlo Giacomo Prato,et al.  Associating Crash Avoidance Maneuvers With Driver Attributes and Accident Characteristics: A Mixed Logit Model Approach , 2012, Traffic injury prevention.